Biomarkers predicting response to 5 immunotherapy arms in the neoadjuvant I-SPY2 trial for early-stage breast cancer (BC): Evaluation of immune subtyping in the response predictive subtypes (RPS).
Authors: Denise M. Wolf, Christina Yau, Michael J. Campbell, Annuska M. Glas, Lorenza Mittempergher, Midas M. Kuilman, Andrei Barcaru, Lamorna Brown Swigart, Rita Nanda, Amy Jo Chien, Lajos Pusztai, Erica Michelle Stringer-Reasor, Rebecca Arielle Shatsky, Claudine Isaacs, Jane Perlmutter, Angela DeMichele, Douglas Yee, Laura Esserman, Laura van 't Veer
Journal: Journal of Clinical Oncology (2023)

102 Background: Previously, we showed that in our first PD1-inhibitor (PD1-inh) arm of I-SPY2, pCR associates with high STAT1/chemokine/dendritic signatures in TN and with high B-cell/low mast cell in HR+. From these results, we defined a research-grade Immune classifier incorporated into the RPS (PMID: 35623341), a schema designed to increase pCR if used to prioritize treatment. A clinical-grade version of the Immune (ImPrint) and other RPS biomarkers are now used in I-SPY2.2. Here we evaluate immune markers in 5 Immune-Oncology (IO) therapy arms (2 PD1-inh, 2 PD1-inh combinations, and 1 PDL1-inh combination). Methods: 343 patients with HER2-negative BC with information on pCR and mRNA in 5 IO arms (n 60-72 pts) plus controls (Ctr: 343) were considered. 32 continuous markers including 30 immune (7 checkpoint genes, 14 immune cell, 3 T/B-cell prognostic, 1 TGFB and 5 tumor-immune) and ESR1/PGR and proliferation signatures, were assessed for association with pCR using logistic regression. p-values were adjusted using the Benjamini-Hochberg method (BH p&lt;0.05). Correlations to multiplex immunofluorescence (mIF) data from our initial arm (immune cell and spatial proximity markers) were calculated. Performance of ImPrint, developed with Agendia Inc, was characterized overall and within HR subsets. Results: A larger number of the research-grade immune markers predict response to IO in HR+ than in TN, with the most for HR+ in combination-IO arms (27/32 biomarkers). Tumor-immune signatures dominated by chemokines/cytokines were most consistently associated with pCR across IO arms and across receptor status. Moreover, we found that these markers correlate to mIF spatial proximity measures reflecting high spatial co-localization of PD1+ immune and PDL1+ tumor cells, in TN especially (r=0.59; p=0.003). The ImPrint classifier was evaluated in the IO arms. In HR+, 28% were ImPrint+; and pCR rates were 76% in ImPrint+ vs. 16% in ImPrint-. In TN, 46% were ImPrint+; and pCR rates were 75% in ImPrint+ and 37% in ImPrint-. Overall (HR+ and TN, in all IO arms), pCR rates were 75% in ImPrint+ and 23% in ImPrint-. Performance varied by arm, with the highest pCR rates for HR+/ImPrint+ &gt;90%; and for TN/ImPrint+ &gt;81%. In contrast, pCR rates in the control arm were 34% for ImPrint+ (HR+:33%; TN: 34%) and 13% for ImPrint- (HR+: 21%; TN:8%). Conclusions: Tumor-immune signaling signatures predict response for IO drug class in both TN and HR+HER2-. The ImPrint single-sample classifier predicts response to a variety of IO regimens in both subsets and may inform prioritization of IO vs other treatments and best balance likely benefit vs risk of serious immune-related adverse events. Clinical trial information: NCT01042379 .